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A workflow for streamlined acquisition and correlation of serial regions of interest in array tomography
BACKGROUND: Array tomography (AT) is a high-resolution imaging method to resolve fine details at the organelle level and has the advantage that it can provide 3D volumes to show the tissue context. AT can be carried out in a correlative way, combing light and electron microscopy (LM, EM) techniques....
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8323292/ https://www.ncbi.nlm.nih.gov/pubmed/34330271 http://dx.doi.org/10.1186/s12915-021-01072-7 |
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author | Gabarre, Sergio Vernaillen, Frank Baatsen, Pieter Vints, Katlijn Cawthorne, Christopher Boeynaems, Steven Michiels, Emiel Vandael, Dorien Gounko, Natalia V. Munck, Sebastian |
author_facet | Gabarre, Sergio Vernaillen, Frank Baatsen, Pieter Vints, Katlijn Cawthorne, Christopher Boeynaems, Steven Michiels, Emiel Vandael, Dorien Gounko, Natalia V. Munck, Sebastian |
author_sort | Gabarre, Sergio |
collection | PubMed |
description | BACKGROUND: Array tomography (AT) is a high-resolution imaging method to resolve fine details at the organelle level and has the advantage that it can provide 3D volumes to show the tissue context. AT can be carried out in a correlative way, combing light and electron microscopy (LM, EM) techniques. However, the correlation between modalities can be a challenge and delineating specific regions of interest in consecutive sections can be time-consuming. Integrated light and electron microscopes (iLEMs) offer the possibility to provide well-correlated images and may pose an ideal solution for correlative AT. Here, we report a workflow to automate navigation between regions of interest. RESULTS: We use a targeted approach that allows imaging specific tissue features, like organelles, cell processes, and nuclei at different scales to enable fast, directly correlated in situ AT using an integrated light and electron microscope (iLEM-AT). Our workflow is based on the detection of section boundaries on an initial transmitted light acquisition that serves as a reference space to compensate for changes in shape between sections, and we apply a stepwise refinement of localizations as the magnification increases from LM to EM. With minimal user interaction, this enables autonomous and speedy acquisition of regions containing cells and cellular organelles of interest correlated across different magnifications for LM and EM modalities, providing a more efficient way to obtain 3D images. We provide a proof of concept of our approach and the developed software tools using both Golgi neuronal impregnation staining and fluorescently labeled protein condensates in cells. CONCLUSIONS: Our method facilitates tracing and reconstructing cellular structures over multiple sections, is targeted at high resolution ILEMs, and can be integrated into existing devices, both commercial and custom-built systems. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12915-021-01072-7. |
format | Online Article Text |
id | pubmed-8323292 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-83232922021-07-30 A workflow for streamlined acquisition and correlation of serial regions of interest in array tomography Gabarre, Sergio Vernaillen, Frank Baatsen, Pieter Vints, Katlijn Cawthorne, Christopher Boeynaems, Steven Michiels, Emiel Vandael, Dorien Gounko, Natalia V. Munck, Sebastian BMC Biol Methodology Article BACKGROUND: Array tomography (AT) is a high-resolution imaging method to resolve fine details at the organelle level and has the advantage that it can provide 3D volumes to show the tissue context. AT can be carried out in a correlative way, combing light and electron microscopy (LM, EM) techniques. However, the correlation between modalities can be a challenge and delineating specific regions of interest in consecutive sections can be time-consuming. Integrated light and electron microscopes (iLEMs) offer the possibility to provide well-correlated images and may pose an ideal solution for correlative AT. Here, we report a workflow to automate navigation between regions of interest. RESULTS: We use a targeted approach that allows imaging specific tissue features, like organelles, cell processes, and nuclei at different scales to enable fast, directly correlated in situ AT using an integrated light and electron microscope (iLEM-AT). Our workflow is based on the detection of section boundaries on an initial transmitted light acquisition that serves as a reference space to compensate for changes in shape between sections, and we apply a stepwise refinement of localizations as the magnification increases from LM to EM. With minimal user interaction, this enables autonomous and speedy acquisition of regions containing cells and cellular organelles of interest correlated across different magnifications for LM and EM modalities, providing a more efficient way to obtain 3D images. We provide a proof of concept of our approach and the developed software tools using both Golgi neuronal impregnation staining and fluorescently labeled protein condensates in cells. CONCLUSIONS: Our method facilitates tracing and reconstructing cellular structures over multiple sections, is targeted at high resolution ILEMs, and can be integrated into existing devices, both commercial and custom-built systems. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12915-021-01072-7. BioMed Central 2021-07-30 /pmc/articles/PMC8323292/ /pubmed/34330271 http://dx.doi.org/10.1186/s12915-021-01072-7 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Methodology Article Gabarre, Sergio Vernaillen, Frank Baatsen, Pieter Vints, Katlijn Cawthorne, Christopher Boeynaems, Steven Michiels, Emiel Vandael, Dorien Gounko, Natalia V. Munck, Sebastian A workflow for streamlined acquisition and correlation of serial regions of interest in array tomography |
title | A workflow for streamlined acquisition and correlation of serial regions of interest in array tomography |
title_full | A workflow for streamlined acquisition and correlation of serial regions of interest in array tomography |
title_fullStr | A workflow for streamlined acquisition and correlation of serial regions of interest in array tomography |
title_full_unstemmed | A workflow for streamlined acquisition and correlation of serial regions of interest in array tomography |
title_short | A workflow for streamlined acquisition and correlation of serial regions of interest in array tomography |
title_sort | workflow for streamlined acquisition and correlation of serial regions of interest in array tomography |
topic | Methodology Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8323292/ https://www.ncbi.nlm.nih.gov/pubmed/34330271 http://dx.doi.org/10.1186/s12915-021-01072-7 |
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